Prognostic value of small nucleolar RNAs (snoRNAs) for colon adenocarcinoma based on RNA sequencing data

GL4SDA: Predicting snoRNA-disease associations using GNNs and LLM embeddings

Small nucleolar RNAs (snoRNAs) play essential roles in various cellular processes, and their associations with diseases are increasingly recognized. Identifying these snoRNA-disease relationships is critical for advancing our understanding of their functional roles and potential therapeutic implications. This work presents a novel approach, called GL4SDA, to predict snoRNA-disease associations using Graph Neural Networks (GNN) and Large Language Models. Our methodology leverages the unique strengths of heterogeneous graph structures to model complex biological interactions. Differently from existing methods, we define a set of features able to capture deeper information content related to the inner attributes of both snoRNAs and diseases and design a GNN model based on highly performing layers, which can maximize results on this representation. We consider snoRNA secondary structures and disease embeddings derived from large language models to obtain snoRNAs and disease node features, respectively. By combining structural features of snoRNAs with rich semantic embeddings of diseases, we construct a feature-rich graph representation that improves the predictive performance of our model. We evaluate our approach using different architectures that exploit the capabilities of many graph convolutional layers and compare the results with three other state-of-the-art graph-based predictors. GL4SDA demonstrates improved scores in link prediction tasks and demonstrates its potential implication as a tool for exploring snoRNA-disease relationships. We also validate our findings through biological case studies about cancer diseases, highlighting the practical application of our method in real-world scenarios and obtaining the most important snoRNA features using explainable artificial intelligence methods.

FXR1 stabilizes SNORD63 to regulate blood-tumor barrier permeability through SNORD63 mediated 2'-O-methylation of POU6F1

How selectively increase blood-tumor barrier (BTB) permeability is crucial to enhance the delivery of chemotherapeutic agents to brain tumor tissues. In this study, we established in vitro models of the blood-brain barrier (BBB) and BTB using endothelial cells (ECs) co-cultured with human astrocytes (AECs) and glioma cells (GECs), respectively. The findings revealed high expressions of the RNA-binding protein FXR1 and SNORD63 in GECs, where FXR1 was found to bind and stabilize SNORD63. Knockdown of FXR1 resulted in decreased expression of tight-junction-related proteins and increased BTB permeability by down-regulating SNORD63. SNORD63 played a role in mediating the 2'-O-methylation modification of POU6F1 mRNA, leading to the downregulation of POU6F1 protein expression. POU6F1 showed low expression in GECs and acted as a transcription factor to regulate BTB permeability by binding to the promoter regions of ZO-1, occludin, and claudin-5 mRNAs and negatively regulating their expressions. Finally, the targeted regulation of FXR1, SNORD63, and POU6F1 expressions, individually or in combination, effectively enhanced doxorubicin passage through the BTB and induced apoptosis in glioma cells. This study aims to elucidate the underlying mechanism of the FXR1/SNORD63/POU6F1 axis in regulating BTB permeability, offering a novel strategy to improve the efficacy of glioma chemotherapy.

Small nucleolar RNA and its potential role in the oncogenesis and development of colorectal cancer

Small nucleolar RNAs (snoRNAs) represent a class of non-coding RNAs that play pivotal roles in post-transcriptional RNA processing and modification, thereby contributing significantly to the maintenance of cellular functions related to protein synthesis. SnoRNAs have been discovered to possess the ability to influence cell fate and alter disease progression, holding immense potential in controlling human diseases. It is suggested that the dysregulation of snoRNAs in cancer exhibits differential expression across various cancer types, stages, metastasis, treatment response and/or prognosis in patients. On the other hand, colorectal cancer (CRC), a prevalent malignancy of the digestive system, is characterized by high incidence and mortality rates, ranking as the third most common cancer type. Recent research indicates that snoRNA dysregulation is associated with CRC, as snoRNA expression significantly differs between normal and cancerous conditions. Consequently, assessing snoRNA expression level and function holds promise for the prognosis and diagnosis of CRC. Nevertheless, current comprehension of the potential roles of snoRNAs in CRC remains limited. This review offers a comprehensive survey of the aberrant regulation of snoRNAs in CRC, providing valuable insights into the discovery of novel biomarkers, therapeutic targets, and potential tools for the diagnosis and treatment of CRC and furnishing critical cues for advancing research into CRC and the judicious selection of therapeutic targets.

Small Nucleolar RNAs as Diagnostic and Prognostic Biomarkers in Cancer: A Systematic Review and Meta-Analysis

OBJECTIVES

Small nucleolar RNAs (snoRNAs) form clusters within the genome, representing a mysterious category of small non-coding RNAs. Research has demonstrated that aberrant snoRNAs can contribute to the development of various types of cancers. Recent studies have identified snoRNAs as potentially valuable biomarkers for the diagnosis or/and prognosis of cancers. However, there has been a lack of comprehensive reviews on prognostic and diagnostic snoRNAs across different types of cancers.

METHODS

We conducted a systematic search of various databases including Google Scholar, Medline, Cochrane, Scopus, PubMed, Embase, ScienceDirect, Ovid-Medline, Chinese National Knowledge Infrastructure, WanFang, and SinoMed with a time frame reception to December 30, 2022. A total of 49 relevant articles were included in our analysis, consisting of 21 articles focusing on diagnostic aspects and 41 articles focusing on prognostic aspects. Pooled odds ratio, 95% confidence intervals (CIs), and hazard ratio (HR) were utilized to evaluate clinical parameters and overall survival (OS), respectively.

RESULT

The findings indicated that area under the curve, sensitivity, and specificity were 0.85, 75%, and 80% in cancer, respectively. There was a possibility that snoRNAs had a positive impact on the diagnosis (risk ratio, RR = 2.95, 95% CI: 2.75-3.16, P = 0.000) and OS (HR = 1) in cancer. Additionally, abnormally expressed snoRNAs were associated with a positive impact on OS time for chronic lymphocytic leukemia (HR: 0.88, 95%Cl: 0.69-1.11, P < 0.00001), colon adenocarcinoma (HR: 0.97, 95%Cl: 0.91-1.03, P < 0.0001), and ovarian cancer (HR: 0.98, 95%Cl: 0.98-0.99, P < 0.00001). However, dysregulated snoRNAs of colon cancer and colorectal cancer had a negative impact on OS time (HR = 3.01 and 1.01 respectively, P < 0.0001).

CONCLUSION

The results strongly suggested that snoRNAs could serve as potential novel indicators for prognosis and diagnosis in cancers. This systematic review followed the guidelines of the Transparent Reporting of Systematic Review and Meta-Analyses (PROSPERO register: CRD42020209096).

Non-coding RNAs as Biomarkers for Survival in Colorectal Cancer Patients

Colorectal cancer (CRC) has a high incidence and fatality rate worldwide. It ranks second concerning death worldwide. Cancer patients are diagnosed with the disease at a later stage due to the absence of early diagnostic methods, which leads to increased death. With the help of recent advancements in the fields of diagnosis and therapy, the development of novel methods using new targets could be helpful for the long-term survival of CRC patients when CRC is detected early. However, the prognosis for the advanced stage of CRC is abysmal. New biomarkers are emerging as promising alternatives since they can be utilized for early detection of CRC, are simple to use, and non-invasive. Non-coding RNAs (ncRNAs) have been seen to have an aberrant expression in the development of many malignancies, including CRC. In the past two decades, much research has been done on non-coding RNAs, which may be valuable as biomarkers and targets for antitumor therapy. Non-coding RNAs can be employed in detecting and treating CRC. Non-coding RNAs play an essential role in regulating gene expression. This article reviews ncRNAs and their expression levels in CRC patients that could be used as potential biomarkers. Various ncRNAs have been associated with CRC, such as microRNAs, long non-coding RNAs, circular RNAs, etc. The expression of these non-coding RNAs may provide insights into the stages of cancer and the prognosis of cancer patients and therefore proper precautionary measures can be taken to decrease cancer-related deaths.

Characterization the prognosis role and effects of snoRNAs in melanoma patients

Melanoma is a melanocyte-derived malignant cancer and is known for its early metastasis and high mortality rates. It is a highly cutaneous tumour disease that could be related to the abnormal immune microenvironment, and the identification of reliable diagnostic and prognostic markers is crucial for improving patient outcomes. In the search for biomarkers, various types of RNAs have been discovered and recognized as reliable prognostic markers. Among these, small nucleolar RNAs (snoRNAs) have emerged as a promising avenue for studying early diagnosis and prognostic markers in tumours due to their widespread presence in tissues, tumour specificity and stability. In our study, we analysed snoRNAs data from melanoma samples in the TCGA-SKCM cohort and developed a prognostic model comprising 12 snoRNAs (SNORD9, SNORA31, SNORD14E, SNORA14A, SNORA5A, SNORD83A, SNORA75, AL096855, AC007684, SNORD14A, SNORA65 and AC004839). This model exhibited unique prognostic accuracy and demonstrated a significant correlation with the immune infiltration tumour microenvironment. Additionally, analysis of the GSE213145 dataset, which explored the sensitivity and resistance of immune checkpoint inhibitors, further supported the potential of snoRNAs as prognostic markers for immunotherapy. Overall, our study contributes reliable prognostic and immune-related biomarkers for melanoma patients. These findings can offer valuable insights for the future discovery of novel melanoma treatment strategies and hold promise for improving clinical outcomes in melanoma patients.

SNORD17-mediated KAT6B mRNA 2'-O-methylation regulates vasculogenic mimicry in glioblastoma cells

Glioblastoma (GBM) is a primary tumor in the intracranial compartment. Vasculogenic mimicry (VM) is a process in which a pipeline of tumor cells that provide blood support to carcinogenic cells is formed, and studying VM could provide a new strategy for clinical targeted treatment of GBM. In the present study, we found that SNORD17 and ZNF384 were significantly upregulated and promoted VM in GBM, whereas KAT6B was downregulated and inhibited VM in GBM. RTL-P assays were performed to verify the 2'-O-methylation of KAT6B by SNORD17; IP assays were used to detect the acetylation of ZNF384 by KAT6B. In addition, the binding of ZNF384 to the promoter regions of VEGFR2 and VE-cadherin promoted transcription, as validated by chromatin immunoprecipitation and luciferase reporter assays. And finally, knockdown of SNORD17 and ZNF384 combined with KAT6B overexpression effectively reduced the xenograft tumor size, prolonged the survival time of nude mice and reduced the number of VM channels. This study reveals a novel mechanism of the SNORD17/KAT6B/ZNF384 axis in modulating VM development in GBM that may provide a new goal for the comprehensive treatment of GBM.

Involvement of the oncogenic small nucleolar RNA SNORA24 in regulation of p53 stability in colorectal cancer

Colorectal cancer (CRC) is a common malignant cancer worldwide. Although the molecular mechanism of CRC carcinogenesis has been studied extensively, the details remain unclear. Small nucleolar RNAs (snoRNAs) have recently been reported to have essential functions in carcinogenesis, although their roles in CRC pathogenesis are largely unknown. In this study, we found that the H/ACA snoRNA SNORA24 was upregulated in various cancers, including CRC. SNORA24 expression was significantly associated with age and history of colon polyps in CRC patient cohorts, with high expression associated with a decreased 5-year overall survival. Our results indicated that the oncogenic function of SNORA24 is mediated by promoting G1/S phase transformation, cell proliferation, colony formation, and growth of xenograft tumors. Furthermore, SNORA24 knockdown induced massive apoptosis. RNA-sequencing and gene ontology (GO) enrichment analyses were performed to explore its downstream targets. Finally, we confirmed that SNORA24 regulates p53 protein stability in a proteasomal degradation pathway. Our study clarifies the oncogenic role of SNORA24 in CRC and advance the current model of the role of the p53 pathway in this process.

Identification of three small nucleolar RNAs (snoRNAs) as potential prognostic markers in diffuse large B-cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is a non-Hodgkin lymphoma with high mortality rates. Small nucleolar RNAs (snoRNAs) are tumor-specific biological markers, but there are few studies on the role of snoRNAs in DLBCL.

MATERIALS AND METHODS

Survival-related snoRNAs were selected to construct a specific snoRNA-based signature via computational analyses (Cox regression and independent prognostic analyses) to predict the prognosis of DLBCL patients. To assist in clinical applications, a nomogram was built by combining the risk model and other independent prognostic factors. Pathway analysis, gene ontology analysis, transcription factor enrichment, protein-protein interactions, and single nucleotide variant analysis were used to explore the potential biological mechanisms of co-expressed genes.

RESULTS

Twelve prognosis-correlated snoRNAs were selected from the DLBCL patient cohort of microarray profiles, and a three-snoRNA signature consisting of SNORD1A, SNORA60, and SNORA66 was constructed. DLBCL patients could be divided into high-risk and low-risk cohorts using the risk model, and the high-risk group and activated B cell-like (ABC) type DLBCL were linked with disappointing survival. In addition, SNORD1A co-expressed genes were inseparably linked to the biological functions of the ribosome and mitochondria. Potential transcriptional regulatory networks have also been identified. MYC and RPL10A were the most mutated SNORD1A co-expressed genes in DLBCL.

CONCLUSION

Put together, our findings explored the potential biological effects of snoRNAs in DLBCL, and provided a new predictor for DLBCL prediction.

Expression profiles of small non-coding RNAs in breast cancer tumors characterize clinicopathological features and show prognostic and predictive potential

Precision medicine approaches are required for more effective therapies for cancer. As small non-coding RNAs (sncRNAs) have recently been suggested as intriguing candidates for cancer biomarkers and have shown potential also as novel therapeutic targets, we aimed at profiling the non-miRNA sncRNAs in a large sample set to evaluate their role in invasive breast cancer (BC). We used small RNA sequencing and 195 fresh-frozen invasive BC and 22 benign breast tissue samples to identify significant associations of small nucleolar RNAs, small nuclear RNAs, and miscellaneous RNAs with the clinicopathological features and patient outcome of BC. Ninety-six and five sncRNAs significantly distinguished (Padj < 0.01) invasive local BC from benign breast tissue and metastasized BC from invasive local BC, respectively. Furthermore, 69 sncRNAs significantly associated (Padj < 0.01) with the tumor grade, hormone receptor status, subtype, and/or tumor histology. Additionally, 42 sncRNAs were observed as candidates for prognostic markers and 29 for predictive markers for radiotherapy and/or tamoxifen response (P < 0.05). We discovered the clinical relevance of sncRNAs from each studied RNA type. By introducing new sncRNA biomarker candidates for invasive BC and validating the potential of previously described ones, we have guided the way for further research that is warranted for providing novel insights into BC biology.

Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study

BACKGROUND

The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking.

RESULTS

We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%.

CONCLUSIONS

Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.

Small Nucleolar RNAs and Their Comprehensive Biological Functions in Hepatocellular Carcinoma

Small nucleolar RNAs (snoRNAs) are a class of highly conserved, stable non-coding RNAs involved in both post-transcriptional modification of RNA and in ribosome biogenesis. Recent research shows that the dysfunction of snoRNAs plays a pivotal role in hepatocellular carcinoma (HCC) and related etiologies, such as hepatitis B virus (HBV), hepatitis C virus (HCV), and non-alcoholic fatty liver disease (NAFLD). Growing evidence suggests that snoRNAs act as oncogenes or tumor suppressors in hepatocellular carcinoma (HCC) through multiple mechanisms. Furthermore, snoRNAs are characterized by their stability in body fluids and their clinical relevance and represent promising tools as diagnostic and prognostic biomarkers. SnoRNAs represent an emerging area of cancer research. In this review, we summarize the classification, biogenesis, activity, and functions of snoRNAs, as well as highlight the mechanism and roles of snoRNAs in HCC and related diseases. Our findings will aid in the understanding of complex processes of tumor occurrence and development, as well as suggest potential diagnostic markers and treatment targets. Furthermore, we discuss several limitations and suggest future research and application directions.

The Potential Role of Small Nucleolar RNAs in Cancers – An Evidence Map

Purpose

Cancer seriously endangers human health in every country of the world. New evidence shows that small nucleolar RNAs play important roles in tumorigenesis. Herein, we created this evidence map to systematically assess the impact of dysregulated snoRNAs on cancers.

Methods

We searched four databases to February 2022 using the keywords, “carcinoma”, “neoplasms”, “tumor”, “cancer”, “snoRNA”, and “small nucleolar rna”. The research data were independently screened by two reviewers. Bubble plot, mind map, heatmap were used to depict the relationship between snoRNAs and cancers.

Results

In total, 102 studies met the inclusion criteria and were analyzed in this evidence map. In this study, we found that dysregulated snoRNAs were statistically associated with the clinicopathological characteristics of cancer patients, and affected tumor cell phenotypes. Abnormally expressed snoRNAs were associated with poor survival in cancer patients. Current research confirmed that snoRNAs have good diagnostic efficiency for cancers. snoRNAs could modulate biological processes and signaling pathways of different cancer cells by altering rRNA, regulating mRNA, and recruiting protein factors.

Conclusion

Taken all together, ectopic snoRNAs may serve as new biomarkers for clinical assessment, diagnostic, prognostic prediction of cancer patients, and provide a potential therapeutic strategy for cancer treatment. This article provided a visual analysis of existing evidence on snoRNAs and cancers, which can offer useful information for different researchers interested in snoRNAs.

Identification of tumour immune infiltration-associated snoRNAs (TIIsno) for predicting prognosis and immune landscape in patients with colon cancer via a TIIsno score model

BACKGROUND

Colon cancer (CC) is the leading cause of tumour-related death worldwide. SnoRNA plays a critical role in the tumour microenvironment. The tumour microenvironment can be shaped by tumour-infiltrating immune cells, which control the destiny of immunotherapy efficacy. This study uniquely focused on snoRNAs derived from immune cells to identify new biomarkers for immune landscape.

METHODS

A novel computational framework was initiated for identifying tumour immune infiltration-associated snoRNAs (TIIsno) signatures and developed a TIIsno score model from integrative snoRNA profiling analysis of 21 purified immune cell lines, 43 colon cancer cell lines, and three datasets (training, test, real-world validation set).

FINDINGS

Our study found that a high TIIsno score was associated with poor CC prognosis. TIIsno scores were seen to be negatively correlated with (I) the infiltration level of most immune cells, (II) the inhibitory immune checkpoints expression level, and (III) the immune score. These findings, taken together with the observation that TIIsno score is lower in MSI-H patients, suggests that patients with a low TIIsno score may have a better response to immunotherapy.

INTERPRETATION

In conclusion, we successfully identified TIIsno and constructed a TIIsno score model, a new potential biomarker of immunotherapy response, which can effectively predict the prognosis of CC patients as well.

FUNDING

National Key R & D Program of China, National Natural Science Foundation of China, key projects from the Nature Science Foundation of Hunan Province, projects from Beijing CSCO Clinical Oncology Research Foundation, Fundamental Research Funds for the Central Universities of Central South University.

Active Enhancer Assessment by H3K27ac ChIP-seq Reveals Claudin-1 as a Biomarker for Radiation Resistance in Colorectal Cancer

Background

Colorectal cancer (CRC) represents the third most common malignant tumor in the worldwide. Radiotherapy is the common therapeutic treatment for CRC, but radiation resistance is often encountered. ChIP-seq of Histone H3K27 acetylation (H3K27ac) has revealed enhancers that play an important role in CRC. This study examined the relationship between an active CRC enhancer and claudin-1 (CLDN1), and its effect on CRC radiation resistance.

Methods

The target CRC genes of active enhancers were obtained from public H3K27ac ChIP-seq, and the genes highly expressed in radio-resistant CRC were screened and intersected with enhancer-driven genes. The clinical roles of CLDN1 in radiation resistance were examined using the t-test, standard mean deviation (SMD), summary receiver operating characteristic curve and Kaplan-Meier curves. The co-expressed genes of CLDN1 were calculated using Pearson Correlation analysis, and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes and Gene Set Variation Analysis (GSVA) analyses were used to examine the molecular mechanisms of CLDN1.

Results

Total 13 703 CRC genes were regulated by enhancers using 58 H3K27ac ChIP-seq. Claudin-1 (CLDN1) was enhancer-driven and notably up-regulated in CRC tissues compared to non-CRC controls, with a SMD of 3.45 (95 CI % = .56-4.35). CLDN1 expression was increased in radiation-resistant CRC with a SMD of .42 (95% CI = .16-.68) and an area under the curve of .74 (95% CI = .70-.77). The cell cycle and immune macrophage levels were the most significant pathways associated with CLDN1.

Conclusion

CLDN1 as an enhancer-regulated gene that can boost radiation resistance in patients with CRC.

Integrative genomic analysis of a novel small nucleolar RNAs prognostic signature in patients with acute myelocytic leukemia

This study mainly used The Cancer Genome Atlas (TCGA) RNA sequencing dataset to screen prognostic snoRNAs of acute myeloid leukemia (AML), and used for the construction of prognostic snoRNAs signature for AML. A total of 130 AML patients with RNA sequencing dataset were used for prognostic snoRNAs screenning. SnoRNAs co-expressed genes and differentially expressed genes (DEGs) were used for functional annotation, as well as gene set enrichment analysis (GSEA). Connectivity Map (CMap) also used for potential targeted drugs screening. Through genome-wide screening, we identified 30 snoRNAs that were significantly associated with the prognosis of AML. Then we used the step function to screen a prognostic signature composed of 14 snoRNAs (SNORD72, SNORD38, U3, SNORA73B, SNORD79, SNORA73, SNORD12B, SNORA74, SNORD116-12, SNORA65, SNORA14, snoU13, SNORA75, SNORA31), which can significantly divide AML patients into high- and low-risk groups. Through GSEA, snoRNAs co-expressed genes and DEGs functional enrichment analysis, we screened a large number of potential functional mechanisms of this prognostic signature in AML, such as phosphatidylinositol 3-kinase-Akt, Wnt, epithelial to mesenchymal transition, T cell receptors, NF-kappa B, mTOR and other classic cancer-related signaling pathways. In the subsequent targeted drug screening using CMap, we also identified six drugs that can be used for AML targeted therapy, they were alimemazine, MG-262, fluoxetine, quipazine, naltrexone and oxybenzone. In conclusion, our current study was constructed an AML prognostic signature based on the 14 prognostic snoRNAs, which may serve as a novel prognostic biomarker for AML.

Screening Plasma Exosomal RNAs as Diagnostic Markers for Cervical Cancer: An Analysis of Patients Who Underwent Primary Chemoradiotherapy

This preliminary study aimed to screen non-coding RNAs (ncRNAs) from plasma exosomes as a new method for cervical cancer diagnosis. Differentially expressed RNAs were initially selected from among a group of 12 healthy individuals (normal group) and a pretreatment group of 30 patients with cervical cancer (cancer group). Then, we analyzed the association between an ncRNA-mRNA network and cancer using ingenuity pathway analysis after secondary selection according to the number and correlation of mRNAs (or ncRNAs) relative to changes in the expression of primarily selected ncRNAs (or mRNAs) before and after chemoradiotherapy. The number of RNAs selected from the initial RNAs was one from 13 miRNAs, four from 42 piRNAs, four from 28 lncRNAs, nine from 18 snoRNAs, 10 from 76 snRNAs, nine from 474 tRNAs, nine from 64 yRNAs, and five from 67 mRNAs. The combination of miRNA (miR-142-3p), mRNAs (CXCL5, KIF2A, RGS18, APL6IP5, and DAPP1), and snoRNAs (SNORD17, SCARNA12, SNORA6, SNORA12, SCRNA1, SNORD97, SNORD62, and SNORD38A) clearly distinguished the normal samples from the cancer group samples. We present a method for efficiently screening eight classes of RNAs isolated from exosomes for cervical cancer diagnosis using mRNAs (or ncRNAs) altered by chemoradiotherapy.